BERT_AugV8_k3_task1_organization_sp040_lw040_fold3

genki10/BERT_AugV8_k3_task1_organization_sp040_lw040_fold3

BERT_AugV8_k3_task1_organization_sp040_lw040_fold3 is a text classification model from genki10. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Mar 25, 2025
Updated: Mar 27, 2025
SHA: 174febc2

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Base models

Model card

From the Hugging Face model README

BERT_AugV8_k3_task1_organization_sp040_lw040_fold3

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.6580
Qwk: 0.1587
Mse: 1.6584
Rmse: 1.2878

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 150

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	3	10.9993	0.0253	10.9976	3.3163
No log	2.0	6	7.3830	0.0	7.3817	2.7169
No log	3.0	9	5.0461	0.0208	5.0450	2.2461
No log	4.0	12	3.4268	0.0	3.4258	1.8509
No log	5.0	15	2.3354	0.0727	2.3345	1.5279
No log	6.0	18	1.8864	0.0549	1.8856	1.3732
No log	7.0	21	1.5282	0.0302	1.5275	1.2359
No log	8.0	24	1.4076	0.0202	1.4069	1.1861
No log	9.0	27	1.5515	0.0488	1.5508	1.2453
No log	10.0	30	1.2856	0.0488	1.2850	1.1336
No log	11.0	33	1.6507	0.0843	1.6500	1.2845
No log	12.0	36	1.7168	0.1669	1.7164	1.3101
No log	13.0	39	1.1605	0.0946	1.1604	1.0772
No log	14.0	42	1.1060	0.2225	1.1061	1.0517
No log	15.0	45	0.9322	0.2900	0.9325	0.9657
No log	16.0	48	1.0099	0.2614	1.0102	1.0051
No log	17.0	51	0.9427	0.2903	0.9431	0.9711
No log	18.0	54	0.9830	0.2787	0.9835	0.9917
No log	19.0	57	1.5100	0.1888	1.5103	1.2289
No log	20.0	60	2.0052	0.1319	2.0053	1.4161
No log	21.0	63	0.9387	0.3619	0.9394	0.9692
No log	22.0	66	1.4726	0.2057	1.4729	1.2136
No log	23.0	69	1.0779	0.2696	1.0783	1.0384
No log	24.0	72	1.3809	0.2425	1.3813	1.1753
No log	25.0	75	1.2372	0.2417	1.2378	1.1126
No log	26.0	78	1.3685	0.2077	1.3688	1.1700
No log	27.0	81	1.4309	0.1521	1.4310	1.1963
No log	28.0	84	1.5781	0.1157	1.5783	1.2563
No log	29.0	87	1.4312	0.1337	1.4315	1.1964
No log	30.0	90	2.2355	0.0757	2.2356	1.4952
No log	31.0	93	1.1609	0.2276	1.1614	1.0777
No log	32.0	96	2.3055	0.0961	2.3057	1.5184
No log	33.0	99	1.2458	0.2201	1.2463	1.1164
No log	34.0	102	1.4763	0.2045	1.4768	1.2153
No log	35.0	105	1.7739	0.1493	1.7744	1.3321
No log	36.0	108	1.6580	0.1587	1.6584	1.2878

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Mar 25, 2025
Updated: Mar 27, 2025